Results for “nemo-evaluator”

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

Index folders of PDFs and other documents into LanceDB for vector search, then query them with semantic search, page filters, verbatim quotes, and cross-document aggregation.

严格细致判断与评分故事文本，从市场潜力、创新属性、内容亮点维度分析质量。适用于小说初筛选、多维度评估打分

Expert technology assessment specialist focused on evaluating, testing, and recommending tools, software, and platforms for business use and productivity optimization

Create, run, and analyze evaluation suites for Microsoft 365 Copilot declarative agents using the @microsoft/m365-copilot-eval CLI.

Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow.

Configure fault tolerance, straggler detection, preemption, in-process restart, and re-run state machine for Megatron Bridge training jobs.

Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.

Guides agents through the full lifecycle of NeMo-RL experiments: understanding recipes, launching reproducible runs, analyzing results, and preserving human oversight with git and TSV logs.

Build and run evaluators for AI/LLM applications using Phoenix, covering error analysis, custom evaluators, experiments, and production monitoring.

Standard reviewer for correctness and reproducibility. Use when the user asks to talk to Omen, requests a code review, or needs reproducibility verification.

GPU-accelerated data curation for LLM training, supporting text, image, video, and audio with fuzzy deduplication, quality filtering, semantic deduplication, PII redaction, and NSFW detection.

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

Augment the standard exec lifecycle with monorepo detection, lane-spec generation, guard validation, and package-scoped dispatch

Expert code reviewer who provides constructive, actionable feedback focused on correctness, maintainability, security, and performance — not style preferences.

Adversarial reviewer that stress-tests claims and conclusions. Use when the user asks to talk to KAY/O, requests an adversarial review, or needs claims validated before publication.

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

Builds, optimizes, and debugs cross-platform mobile applications with React Native and Expo, covering navigation, native modules, list performance, and platform-specific code.

Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.

Orchestrates three frontier models to debate a question and synthesizes their best insights into a single superior answer.

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.

针对 Modular RAG MCP Server 项目的老师式复习 Agent。按章节带领用户系统复习项目知识点，每道题互动问答、给出参考答案，复习结束后记录掌握进度，每次开始时回顾上次进度并建议继续或复习。Use when user says '复习项目', '帮我复习', '带我复习', '开始复习', '项目复习', 'review project', 'study review', '学习复习', '复盘', or wants to systematically review and study the project.

依据竖屏短剧评估标准，从核心爽点、故事类型等维度评估打分。适用于评估故事改编为竖屏短剧的潜力、分析市场竞争力

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

Assesses new tools, technologies, and integration options for adoption, comparing vendors and recommending implementations.

LLaVA-Critic: Learning to Evaluate Multimodal Models

A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.

Evaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a winner among completed AgentHub agents.

Fine-tune, evaluate, run inference, and export Cosmos-Embed1 video-text embedding models for tasks like text-to-video retrieval and semantic deduplication.

Every metric encodes an opinion about which mistake hurts.

杰诺斯（少年漫）认知与表达框架（压缩蒸馏）：改造人认真、战损美学、师徒忠犬 触发：一拳超人 等。虚构

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy (see `emil-design-eng`). Default to flagging; approval is earned. Use when reviewing a diff for motion quality — not for writing features, fixing unrelated bugs, or general (non-motion) code review. For building an animation from scratch, use `animate`; for a whole-codebase audit, use `improve-animations`. Source: github.com/emilkowalski/skills.